Cerca risorse accademiche

Artificial Intelligence (AI) is increasingly recognized as a transformative tool in the field of radiation and nuclear safety. This technology offers significant opportunities to enhance the safety, security, efficiency,...

The Artificial Intelligence (AI) revolution, in its different manifestations -expert systems, neural networks, intelligent hybrid systems, etc.- brings with it many technological advances. Although this technology has so...

A search process implies an exploration of new, unvisited states. This quest to find something new tends to emphasize the processes of change. However, heuristic search is different from random search because features ...

In a highly competitive market, BT1 faces tough challenges as a service provider for telecommunication solutions. A proactive approach to the management of its resources is absolutely mandatory for its success. In this p...

In this paper, we solve some benchmarks of Set Covering Problem and Equality Constrained Set Covering or Set Partitioning Problem. The resolution techniques used to solve them were Ant Colony Optimization algorithms and ...

We present the results of our work on applying genetic algorithms combined with a discrete event simulation to the problem of convoy scheduling. We show that this approach can automatically remove conflicts from a convoy...

In a highly competitive market, BT1 faces tough challenges as a service provider for telecommunication solutions. A proactive approach to the management of its resources is absolutely mandatory for its success. In this p...

This paper presents a new traffic engineering multitreemultiobjective multicast routing algorithm (M-MMA) that solves for the first time the GMM model for Dynamic Multicast Groups. Multitree traffic engineering uses seve...

Scheduling is an active area of research in applied artificial intelligence. Scheduling problems typically comprise several concurrent (and often conflicting) goals, and several resources which may be allocated in order ...

In dynamic scheduling arrival times as well, as some or all job attributes are unknown in advance. Dynamism can be classified as partial or total. In simplest partially dynamic problems the only unknown attribute of a j...

In this preliminary study the Flow Shop Scheduling Problem (FSSP) is solved by hybrid Evolutionary Algorithms. The algorithms are obtained as a combination of an evolutionary algorithm, which uses the Multi-Inver-Over op...

In a production system it is usual to stress minimum tardiness to achieve higher client satisfaction. According to the client relevance, job processing costs and requirements, and various other considerations, a weight ...

Evolutionary algorithms (EAs) can be used as optimisation mechanisms. Based on the model of natural evolution, they work on populations of individuals instead of on single solutions. In this way, the search is performed ...

Instances of static scheduling problems can be easily represented as graphs where each node represents a particular operation. This property makes the Ant Colony Algorithms well suited for different kinds of scheduling p...

In this paper we describe a computer system that calculates allocation to claims according to two kinds of bankruptcy rules. The first kind implemented are those whose results corresponds to the classical solutions of ga...

Evolutionary Computation (EC) have been applied to a great number of optimisation problems with some success, specially in fields such as production operations in manufacturing industry, parallel and distributed systems,...

Parallel machine scheduling, involves the allocation of jobs to the system resources (a bank of machines in parallel). A basic model consisting of m machines and n jobs is the foundation of more complex models. Here, job...

Evolutionary algorithms (EAs) offer a robust approach to problem solving. EAs are extremely flexible and can be extended by incorporating alternative approaches to favour he search process. One way is to hybridize an evo...

The choice of a search algorithm can play a vital role in the success of a scheduling application. Evolutionary algorithms (EAs) can be used to solve this kind of combinatorial optimization problems. Compared to conventi...

The travelling salesman problem (TSP) is a NP-hard problem. Techniques as either Branch and Bound or Dynamic Programming supplied the global optimum solution for instances with more than 7000 cities. But, ther needed mor...

Evolutionary algorithms (EAs) have been successfully applied to scheduling problems. Current improvements towards convergence issues in EAs include incest prevention and multiplicity features. A multiplicity feature all...

A new issue for combinatorial optimization problems is to incorporate local search into the framework of evolutionary algorithms, leading to hybrid evolutionary algorithms. With the hybrid approach, evolutionary algorith...

Evolutionary algorithms (EAs) are merely blind search algorithms, which only make use of the relative fitness of solutions, but completely ignore the nature of the problem. Their performance can be improved by using new ...

The Flow Shop Scheduling Problem have been tackled using different techniques which goes from mathematical techniques like Branch and Bound to metaheuristics like evolutionary algorithms (EAs). Although in the real worl...